Package: ModalForecast 0.1.0

Christian Galarza

ModalForecast: Parametric Modal ARIMA Models using the SKD Family

Implements parametric modal Autoregressive Integrated Moving Average (ARIMA) models utilizing the Skewed Distribution (SKD) family. Current distributions supported are the Skew-Normal, Skewed Student-t, and Skewed Laplace. The conditional mode is parameterized and optimized via maximum likelihood using analytical gradients. Includes comprehensive residual diagnostics, robustness options (heavy tails, asymmetry), robust parametric bootstrap prediction intervals, and classical asymptotic inference via the Fisher Information matrix. Methods are described in Galarza, C.E., Lachos, V.H., Cabral, C.R.B., & Castro, L.M. (2017) <doi:10.1002/sta4.140>.

Authors:Christian Galarza [aut, cre]

ModalForecast_0.1.0.tar.gz
ModalForecast_0.1.0.tar.gz(r-4.7-any)ModalForecast_0.1.0.tar.gz(r-4.6-any)
ModalForecast_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
ModalForecast/json (API)
NEWS

# Install 'ModalForecast' in R:
install.packages('ModalForecast', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/chedgala/modalforecast/issues

On CRAN:

Conda:

1.70 score 5 exports 32 dependencies

Last updated from:8d30c72324. Checks:4 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK156
source / vignettesOK193
linux-release-x86_64OK160
wasm-releaseOK129

Exports:auto.modal.arimadiagnosticsenvelopefit_modal_arimaforecast

Dependencies:clicolorspacecpp11farverforecastfracdiffgenericsggplot2gluegridExtragtableisobandlabelinglatticelifecyclelmtestmagrittrnlmennetR6RColorBrewerRcppRcppArmadillorlangS7scalestimeDateurcavctrsviridisLitewithrzoo